Doctor of Philosophy, The Ohio State University, 2021, Electrical and Computer Engineering
In applications such as networked monitoring and control
systems, wireless sensor networks, and autonomous vehicles, it is crucial for the destination node to receive timely status updates so that it can make accurate decisions. For example, a moving car with a speed of 65 mph will traverse almost 29 meters in 1 second, and hence, stale information (regarding the location of surrounding vehicles, velocities, etc.) has a dramatic serious impact on this situation. Age of information (AoI), or simply age, has been used to measure the freshness of status updates. More specifically, AoI is the age of the freshest update at the destination, i.e., it is the time elapsed since the freshest received update was generated. It should be noted that optimizing traditional network performance metrics, such as throughput or delay, does not attain the goal of timely updating. For instance, it is well known that AoI could become very large when the offered load is high or low. In other words, AoI captures the information lag at the destination, and is hence more apt for achieving the goal of timely updates.
In this thesis, we leverage rigorous theory to develop low-complexity scheduling algorithms that are apt for a wide range of information update systems. In particular, we consider the following systems:
-Information update systems with stochastic packet arrivals: We consider single and multihop networks with stochastic arrivals, where our goal is to answer the following fundamental questions: (i) Which queueing discipline can minimize the age? And (ii) under what conditions is the minimum age achievable? Towards this goal, we design low-complexity scheduling policies to achieve (near) age-optimality in single and multihop networks with single source. The achieved results that we present here hold under quite general conditions, including (i) arbitrary packet generation and arrival processes, (ii) for minimizing both the age processes in stochastic ordering and any non-d (open full item for complete abstract)
Committee: Ness Shroff (Advisor); Yin Sun (Other); Atilla Eryilmaz (Committee Member); Abhishek Gupta (Committee Member); Qin Ma (Committee Member)
Subjects: Communication; Computer Engineering; Electrical Engineering